langchain-agent-setup

What problem does it solve?

This skill provides configuration and extension patterns for building Gemini-powered LangChain agents, enabling teams to quickly customize LLM-driven assistants with new capabilities while keeping a clean architecture.

Core Features & Use Cases

• LLM Initialization: Standardized initialization of Gemini models via LangChain, with a consistent API.
• Capability Extension: Add new capabilities as methods on the GeminiLLM class and hook them into an orchestrator.
• System Prompt Customization: Centralized pattern for defining and switching system prompts based on session type or task.
• End-to-End Orchestration: Clear separation between LLM wiring, capability orchestration, and front-end/backend flow for deterministic responses.

Quick Start

Configure a GeminiLLM instance with a Gemini model, implement a new capability as a method on the LLM class, and wire it into the InterviewOrchestrator to handle a new task.